Pacesetter, Inc.

St. Jude Medical Ab

Jay Snell

Bing Zhu

Laleh Jalali

Katie Hoberman

Gene A Bornzin

Xiaoyi Min

Jeffery D Snell

Peter Boileau

Josh Reiss

Elizabeth Bacon

Jong Gill

Eric Steven Fain

Rupinder Bharmi

Anders Bjorling

Eliot L Ostrow

Mary Elizabeth Bush

Harish Krishnaswamy

Mohssen Fard

An exemplary method includes receiving a signal from an intrathoracic vibration sensor, analyzing the signal for vibration associated with deceleration of blood flow into the left ventricle, based at least in part on the analyzing, deciding whether to call for adjustment to one or more parameters of a bi-ventricular pacing therapy. Other exemplary methods, devices, systems, etc., are also disclosed.

Use of cardiohemic vibration for pacing therapies

The present invention relates to an improved medical device and method for accurately and reliably determining a cardiac status of a patient. An implantable medical device, IMD, comprises a sensor arrangement adapted to sense signals related to mechanical activity of the heart and an activity level sensor arrangement adapted to sense an activity level of the patient. Further, the IMD calculates a percentage of left ventricular diastolic time (PLVDT) for a cardiac cycle corresponding to a relation between a diastolic time interval and a cardiac cycle time interval using the determined systolic and diastolic time intervals or a percentage of left ventricular systolic time (PLVST) for a cardiac cycle corresponding to a relation between a systolic interval time interval and a cardiac cycle time interval. A cardiac status is determined based on the calculated PLVDT (or PLVST) and on an activity level of the patient.

Devices and method for determining and monitoring a cardiac status of a patient by using PLVDT or PLVST parameters

A method and system are provided for trending a coronary burden such as an ischemic burden or acute myocardial infarction (AMI) for a patient. Trending provides obtaining cardiac data over a period of time, identifying the onset and the termination of coronary episodes based on a ST segment variation within the cardiac data, recording coronary burden information, and presenting the coronary burden information to a user. The coronary burden information may include the number of coronary episodes occurring over a period of time, the time duration of the coronary episodes, and the maximum ST segment variations for the coronary episodes that occur over a period of time.

Methods and systems for trending ST segment changes over time

Cardiac activity is sensed over a plurality of heart beats defining a beat set. For each beat in the set, it is determined whether the beat is a non-classified beat (e.g., paced beat, a beat outside of a specified heart rate range or a PVC), or a classified beat. For each classified beat, it is determined whether the beat is a non-detect beat, a minor beat or a major beat. Counts of classified beats, non-classified beats, major beats, minor beats, and non-detect beats are maintained. The beat set is declared to be one of a non-classified set, a major set, a minor set or a non-detect set based on the relative counts of classified beats, non-classified beats, major beats, minor beats, and non-detect beats. Over a period of time, counts of beat-set types are maintained and entry into and exit from ST episodes are determined based on these beat-set counts.

Systems and methods related to ST segment monitoring by an implantable medical device

Exemplary systems, devices, and methods pertaining to cardiac related therapy and particularly to interferential cardiac preconditioning and depolarization are described. A cardiac arrhythmia is detected from electrogram data sensed from a patient's heart and a region of the heart affected by the cardiac arrhythmia is determined. The affected region is interferentially energized by multiple cycles of two concurrently delivered alternating currents which are offset in frequency.

Interferential cardiac preconditioning and depolarization

Techniques are described for generating diagnostic information to aid in determining whether cardiac ischemia within a patient is clinically actionable. In one example, a pacemaker or implantable cardioverter/defibrillator (ICD) detects information pertaining to arrhythmia precursors and to episodes of sustained arrhythmias, as well as information pertaining to episodes of cardiac ischemia. The implanted device then correlates the arrhythmia precursors and the sustained arrhythmias with the episodes of cardiac ischemia so as to generate diagnostics permitting a physician reviewing the diagnostics to determine whether the ischemia is clinically actionable. In some implementations, the diagnostics are instead generated by an external system based on raw data provided by the implanted device. In some implementations, the device itself determines whether the ischemia is clinically actionable and automatically controls therapy or generates warning signals accordingly.

System and method for generating and using cardiac ischemia diagnostics based on arrhythmia precursors and arrhythmia episodes

A method and system are provided for trending variation in coronary burden across multiple heart rate ranges. The method and system include obtaining cardiac signals having a segment of interest over a period of time where each cardiac signal has an associated heart rate that falls within at least one heart rate range. Segment variations of the segment of interest are determined and grouped based on the associated heart rates to produce distributions of segment variations that are associated with the heart rate ranges. Trending information is produced by automatically comparing the distributions of segment variations between different heart rate ranges.

Method and system for trending variation in coronary burden across multiple heart rate ranges

Techniques are described for adaptively adjusting detection thresholds for use in detecting cardiac ischemia and other abnormal physiological conditions based on morphological parameters derived from intracardiac electrogram (IEGM) signals, impedance measurements, or other signals. In one example, where ST segment elevation is used to detect cardiac ischemia, default detection thresholds are determined in advance from an examination of variations in ST segment elevations occurring within a population of patients. Thereafter, an individual pacemaker or other implantable medical device uses the default thresholds during an initial learning period to detect ischemia within the patient in which the device is implanted. During the initial learning period, the pacemaker also collects data representative of the range of variation in ST segment elevations occurring within the patient. The pacemaker then adaptively adjusts the thresholds based on the range of variation so as to improve detection specificity within the patient.

System and method for adaptively adjusting cardiac ischemia detection thresholds and other detection thresholds used by an implantable medical device

Techniques are described for efficiently detecting and distinguishing among cardiac ischemia, hypoglycemia or hyperglycemia based on intracardiac electrogram (IEGM) signals. In one example, a preliminary indication of an episode of cardiac ischemia is detected based on shifts in ST segment elevation within the IEGM. In response, the implanted device then records additional IEGM data for transmission to an external system. The external system analyzes the additional IEGM data to confirm the detection of cardiac ischemia using a more sophisticated analysis procedure exploiting additional detection parameters. In particular, the external system uses detection parameters capable of distinguishing hypoglycemia, hyperglycemia and hyperkalemia from cardiac ischemia, such as QTmax and QTend intervals. Alternatively, the more sophisticated analysis procedure may be performed by the device itself, if it is so equipped. Other examples described herein pertain instead to the detection of atrial fibrillation.

System and method for efficiently distinguishing among cardiac ischemia, hypoglycemia and hyperglycemia using an implantable medical device and an external system

A method and system are provided for tracking ST shift data. The system includes an implantable medical device having an input configured to receive cardiac signals. Each cardiac signal has an associated heart rate and includes a segment of interest. The implantable medical device further includes a processor configured to determine segment variations of the segment of interest in the cardiac signals. The processor determines a heart rate associated with each of the segment variations with each heart rate falling within a corresponding heart rate range. The implantable medical device also includes a memory configured to store a group of histograms for a corresponding group of heart rate ranges. The histograms store distributions for the segment variations within corresponding heart rate ranges.

System and method for tracking ST shift data utilizing histograms

A method and apparatus for analyzing IEGM waveforms is disclosed. The method includes generating a long term ensemble average of a plurality of baseline IEGM waveforms and generating a short term ensemble average of at least a portion of the plurality of baseline IEGM waveforms. The method further includes determining a short term absolute point value as a function of the absolute value of the difference of the amplitude of the short term ensemble average and a test IEGM waveform and a long term absolute point value as a function of the difference of the amplitude of the long term ensemble average and the test waveform at a plurality of sample points. The disclosed method further includes detecting ischemia if the difference between the short term absolute point value and the long term absolute point value is greater than an ischemia detection threshold.

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Studio City, CA, United States of America

Jay Snell